Detecting the Hidden: A Comprehensive Review of MP3 Steganalysis Techniques

Detecting the Hidden: A Comprehensive Review of MP3 Steganalysis Techniques | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Detecting the Hidden: A Comprehensive Review of MP3 Steganalysis Techniques Stella J, Karthikeyan P This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6588907/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract MP3 is among the most widely adopted audio formats worldwide, frequently utilized in mobile and multimedia applications. Unfortunately, cybercriminals—such as hackers, hacktivists, and terrorist groups—have exploited this format by embedding steganographic content into MP3 files, rendering hidden information imperceptible to casual inspection. Steganography involves concealing secret messages within an audio cover file, enabling covert communication, whereas steganalysis refers to the detection and extraction of such hidden data. Traditional steganalysis methods primarily depend on statistical techniques to identify anomalies within the audio bitstream. Recent advancements, however, have introduced deep learning approaches capable of detecting subtle changes and complex patterns in audio signals. This review examines key aspects of MP3 steganalysis, including dataset selection, feature extraction, and detection methodologies, drawing on both statistical and deep learning-based frameworks. Effective analysis hinges on extracting spectral, temporal, and statistical features while addressing challenges such as compression artifacts, variable encoding parameters, and fluctuating bitrates. Despite considerable progress, significant research gaps remain—particularly in detecting low-capacity embeddings, adapting to variable sample lengths, and ensuring model generalization across diverse MP3 encoding formats. Notably, this study is grounded in a comprehensive analysis of high-quality research articles published in reputable databases such as IEEE Xplore, Scopus, and Web of Science, ensuring the reliability and relevance of the findings. To further advance MP3 steganalysis, future work must focus on curating diverse datasets, refining feature extraction strategies, and developing hybrid detection models to enhance forensic robustness. Theoretical Computer Science Digital Forensics MP3 Payload detection CNN Stego artifacts Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6588907","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":451674371,"identity":"6fae19e7-1843-415e-811c-bb012951b943","order_by":0,"name":"Stella J","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIie2PuwrCMBRAEy7UpTrror8QcRJ8/Eok4KTgKDgYKNSl2rVO/oWzIYOL4Adk0T+IWxEHr4/FwXQVzBna03JPe0OIx/ODUImX0+QhVO4sPgSlwgQI4ewpSmWPBAr/805wVujw/cIdpEd14qyHcmC6c902KkCovYwci2UCGGcCZcT0eGWaMRCorbeuBIIqZ/jlLMQkMRSTAMquJNWlnLM5Ci7WTky/OJEiwONrlCHXJDeD4iQTLVxsH6Ls1FIaEQONnGdppups7XRWR4lsfjPdzSJS9uJK5OsePoXGr2W/zyONT7k5hz0ej+dPuQNQrlFoy/L7VgAAAABJRU5ErkJggg==","orcid":"","institution":"Anna University","correspondingAuthor":true,"prefix":"","firstName":"Stella","middleName":"","lastName":"J","suffix":""},{"id":451674394,"identity":"53dc210a-a037-4eac-8363-05591cb87ff7","order_by":1,"name":"Karthikeyan P","email":"","orcid":"","institution":"Velammal College of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Karthikeyan","middleName":"","lastName":"P","suffix":""}],"badges":[],"createdAt":"2025-05-04 14:34:12","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6588907/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6588907/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82023786,"identity":"a1ad42c5-82d8-407c-88c9-63e99ca62202","added_by":"auto","created_at":"2025-05-06 06:14:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1823220,"visible":true,"origin":"","legend":"","description":"","filename":"mp3forensicinvestigation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6588907/v1_covered_909e36c8-927a-4975-888e-aa4935257e33.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eDetecting the Hidden: A Comprehensive Review of MP3 Steganalysis Techniques\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Velammal college of Engineering and Technology","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Digital Forensics, MP3, Payload detection, CNN, Stego artifacts","lastPublishedDoi":"10.21203/rs.3.rs-6588907/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6588907/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMP3 is among the most widely adopted audio formats worldwide, frequently utilized in mobile and multimedia applications. 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